Introduction
1. Introduction
Filtering by row
Extracting data by column
Practice using filter() and select()
The pipe operator
Sorting rows
Summary

Instruction

In this chapter, we'll focus on new ways of wrangling data and computing statistics using tidyverse's dplyr package. It contains functions that filter rows, select columns, group data, and compute statistics. If you know SQL, dplyr will come easy: it was inspired by SQL.

As usual, we'll start by examining our data. This time, we'll be dealing with country data, including country names, populations, and areas.

Exercise

Use glimpse() to check the structure of the countries dataset.

Stuck? Here's a hint!

Type:

glimpse(countries)